SoftmaxRegressionNNImpactDetection.py 文件源码

def _yield_minibatches_idx(self, n_batches, data_ary, shuffle=True):
            indices = np.arange(data_ary.shape[0])
            if shuffle:
                indices = np.random.permutation(indices)
            if n_batches > 1:
                remainder = data_ary.shape[0] % n_batches

                if remainder:
                    minis = np.array_split(indices[:-remainder], n_batches)
                    minis[-1] = np.concatenate((minis[-1],
                                                indices[-remainder:]),
                                               axis=0)
                else:
                    minis = np.array_split(indices, n_batches)

            else:
                minis = (indices,)

            for idx_batch in minis:
                yield idx_batch